change loadig subtasks

src/lerobot/policies/sarm/modeling_sarm.py

@@ -283,18 +283,24 @@ class SARMRewardModel(PreTrainedPolicy):
     def _update_num_stages_from_dataset(self, dataset_meta) -> None:
         """Update num_stages in config based on dataset subtask annotations."""
         episodes = dataset_meta.episodes
-        if "annotation.subtask.name" not in episodes:
-            raise ValueError("No subtask annotations found in dataset annotations")
+        if episodes is None or len(episodes) == 0:
+            raise ValueError("No episodes found, using default num_stages")
             
+        if 'subtask_names' not in episodes.column_names:
+            raise ValueError("No subtask annotations found in dataset, using default num_stages")
+
+        episodes_df = episodes.to_pandas()
+        
+        # Collect all unique subtask names
         all_subtask_names = set()
-        for i in range(len(episodes["annotation.subtask.name"])):
-            subtask_names = episodes["annotation.subtask.name"][i]
-            if subtask_names:
-                for name in subtask_names:
-                    all_subtask_names.add(name)
+        for ep_idx in episodes_df.index:
+            subtask_names = episodes_df.loc[ep_idx, 'subtask_names']
+            if subtask_names is None or (isinstance(subtask_names, float) and pd.isna(subtask_names)):
+                continue
+            all_subtask_names.update(subtask_names)
         
         if not all_subtask_names:
-            raise ValueError("No subtask names found in dataset annotations")
+            raise ValueError("No valid subtask names found, using default num_stages")
         
         # Sort subtask names for consistent ordering
         subtask_names = sorted(list(all_subtask_names))